Skip to content
GCC AI Research

Search

Results for "threat analysis"

Security-Enhanced Radio Access Networks for 5G OpenRAN

MBZUAI ·

Dr. Zhiqiang Lin from Ohio State University presented the Security-Enhanced Radio Access Network (SE-RAN) project to address cellular network threats using O-RAN. The project includes 5G-Spector, a framework for detecting L3 protocol exploits via MobiFlow and MobieXpert, and 5G-XSec, a framework leveraging deep learning and LLMs for threat analysis at the network edge. Dr. Lin also outlined a vision for AI convergence with cellular security for enhanced threat detection. Why it matters: Enhancing 5G security through AI and open architectures is critical for protecting next-generation mobile networks in the GCC region and globally.

Analyzing Threats of Large-Scale Machine Learning Systems

MBZUAI ·

A PhD candidate from the University of Waterloo presented on threats from large machine learning systems at MBZUAI. The talk covered data privacy during inference and the misuse of ML systems to generate deepfakes. The speaker also analyzed differential privacy and watermarking as potential solutions. Why it matters: Understanding and mitigating the risks of large ML systems is crucial for responsible AI development and deployment in the region.